This paper presents a set of geometric signature features for offline automatic signature verification based on the description of the signature envelope and the interior stroke distribution in polar and Cartesian coordinates. The features have been calculated using 16 bits fixed-point arithmetic and tested with different classifiers, such as hidden Markov models, support vector machines, and Euclidean distance classifier. The experiments have shown promising results in the task of discriminating random and simple forgeries.
No takes yet. Share an insight, caveat, or question.
Ferrer et al. (2005) studied this question.
Synapse has enriched 2 closely related papers on similar clinical questions. Consider them for comparative context: